The article presents a new method for identifying chaotic behavior in time series data. By using statistics from correlation dimension and considering the ergodicity of chaos, the researchers developed a more accurate way to calculate the largest Lyapunov exponent. This approach improves upon previous methods and enhances our ability to analyze, predict, and control nonlinear systems.